To help build the world’s most powerful offshore wind platform, GE Renewable Energy tapped into the broad, multidisciplinary skill sets of GE Research's innovation engine.

GE researchers partnering with Intel, Florida State University and Baker Hughes on $5.2 M program with the US Department of Energy to develop new cyber protection capabilities

Dr. Ghaemi received the Ph.D. degree in electrical engineering and the M.S. degree in mathematics from University of Michigan in 2010 and 2009 respectively. He was a visiting scholor at ETH in 2008. From 2010 to 2012 he was a post-doctoral associate in the Mechanical Engineering department at MIT, researching supervisory control of order-preserving systems and stochastic analysis of biological systems.

Putting optimal back on the table for real applications using Quantum as an accelerator

Keeping workers safe through analytics derived from sensor data fusion & aggregation and delivered through pervasive connectivity & real-time visualization

Leveraging time-sensitive quantum key distribution technology to provide industrial and utility networks with simpler, more deterministic, and secure communication.

Stephen F. Bush is a researcher in Algorithmic Communications Network Theory at GE Research. Dr. Bush was presented with a Gold Cup Trophy Award from DARPA for his work in fault tolerant networking. Stephen F. Bush received the B.S. degree in electrical and computer engineering from Carnegie Mellon University, M.S. degree in computer science from Cleveland State University, and Ph.D. degree from the University of Kansas. He is currently a researcher at General Electric’s Research Center in Niskayuna, NY.

GE Research is giving EEDP participants an intimate look at the GE technologies that are disrupting industrial ecosystems.

Dr. Naresh Iyer is a Principal Scientist in the AI and Machine Learning group at GE Research. He has 20 years of experience in the research and application of machine learning to a variety of industry problems, including asset life prognostics, surrogate modeling, multi-objective optimization and decision making under uncertainty. He has developed solutions for a diverse range of industrial applications using methods in supervised, unsupervised, semi-supervised learning and evolutionary soft computing. 

Karla is an electrical engineer who, at a young age, was drawn to the beauty of math and science.